Scenic:

An Open-Source Probabilistic Programming System for Data Generation and Safety in AI-Based Autonomy

2024 Scenic Workshop

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Abstract


We invite you to join us on August 26-27 for a workshop for current and potential users and developers of the Scenic Scenic probabilistic programming language for world modeling and data generation for AI-based autonomy.

The workshop will be hosted at UC Santa Cruz, and will include food and housing from dinner on August 25 through lunch on August 28. The two main days of the workshop (26th and 27th) will provide hands-on tutorials on the Scenic language, how to interface it to your simulator of choice, and Scenic's use cases for testing, debugging, synthetic data generation, etc. We will also have breakout groups on topics of special interest such as Scenic's internals and application domains including autonomous driving and robotics.

Flexible Scenario / Data Generation Across Different Domains


Autonomous Vehicles

Robotics

Aviation

Reinforcement Learning

Augmented Reality

Overview


Today's autonomous systems rely heavily on the use of machine learning components trained on large amounts of data. Even so, it is expensive to collect relevant data and test these systems in the real world in a manner that captures typical data distributions and also covers edge cases. Therefore, simulators are widely adopted in the robotics and computer vision community to train, test, and debug autonomous and semi-autonomous systems. However, working directly with simulators can be too low-level and problem-specific. To support the design lifecycle of autonomous/semi-autonomous systems, one needs to raise the level of abstraction above individual simulators and provide a formal framework for world modeling. Such a world model can help reason about the safety of a system and facilitate data generation and sim-to-real validation, as well as help to interpret, validate, share, or re-use training and test scenarios across the community.

The objective of this tutorial is to introduce Scenic, an open-source, domain-specific probabilistic programming language for world modeling that addresses the above needs. Scenic is designed to model and generate interactive (or reactive), multi-agent scenarios in a manner portable to any simulator. In Scenic, users can precisely model a stochastic environment in which an autonomous/semi-autonomous system operates, can perform a variety of design and analysis tasks, and can communicate them as interpretable programs. Scenic has a variety of demonstrated use cases, including synthetic data generation, data augmentation, debugging and retraining and redesign of perception components, sim-to-real validation, testing safety of autonomous system both in simulation and in the real world, training reinforcement learning agents in multiplayer settings, and more. To achieve these goals, Scenic has been designed to be (i) intuitive to learn, (ii) probabilistic to capture the uncertainty and stochasticity in the real world, (iii) simulator-agnostic, and (iv) open-source and in the public domain for external members to contribute.

Logistics

Virtual Attendance:

In-Person Attendance:

Schedule


Sunday, August 25: (for those arriving the evening before the workshop)

Monday, August 26: (main workshop day 1)

Tuesday, August 27: (main workshop day 2)

Wednesday, August 28: (optional morning session)

For details, please contact Daniel Fremont.
Website template by Oriane Siméoni from the Object localization for free CVPR '23 tutorial.